1. |
- Kruse, S.A., et al.
(author)
-
Socioeconomic indicators as a complement to life cycle assessment : An application to salmon production systems
- 2009
-
In: The International Journal of Life Cycle Assessment. - : Springer Science and Business Media LLC. - 0948-3349 .- 1614-7502. ; 14:1, s. 42234-
-
Journal article (peer-reviewed)abstract
- Background, aim, and scope: There is a growing recognition on the part of industry, policymakers, and consumers that sustainable industry practices are needed to maintain environmental and social well being. Life cycle assessment (LCA) is an internationally standardized analytical framework that has traditionally focused on evaluation of the environmental impacts of processes or products using a cradle-to-grave approach. Yet, sustainability, defined generally, requires that assessments consider not only environmental but also social and economic impacts-the other two pillars of sustainability. Even though the LCA methodology has the potential to include both social and economic indicators, and SETAC guidelines recommend the inclusion of such impact categories in all detailed LCAs, no established set of metrics exists to describe the relationship between socioeconomic indicators (SEIs) and a specific product or process; nor is there a common understanding on how such metrics might be developed. This article presents the methods for and development of a suite of socioeconomic indicators that complement the LCA methodology and provides a comprehensive approach for assessing the cradle-to-grave sustainability of a product or process. Methods: A combined top-down and bottom-up approach serves as the basis for development of the set of socioeconomic indicators presented here. Generally recognized societal values, industry specific issues, and financial constraints associated with collection of data necessary for measurement of the indicators are all factors considered in this approach. In our categorization, socioeconomic indicators fall into two types: additive indicators and descriptive indicators. Results: Indicators are categorized based on fundamental methodological differences and then used to describe the socioeconomic impacts associated with salmon production. Additive indicators (e.g., production costs and value added) and descriptive indicators (e.g., fair wage and contribution to personal income) are both discussed. Discussion: There is a need to further develop and refine methods to assess the results of socioeconomic indicators using a life cycle perspective. It would be most interesting to conduct additional case studies that focus on such methodological development, particularly trade-offs between stakeholder groups and pillars of sustainability. Additional areas of discussion are (1) the need for data to populate socioeconomic indicators and (2) defining system boundaries for socioeconomic indicators. Conclusions: This article presents a set of socioeconomic indicators designed to serve as a complement for the LCA framework, thus, increasing the framework's effectiveness as a measure of the overall sustainability of a product or process. Development of socioeconomic indicators as a complement to LCA is still in its early stages, however, and further research is required. Recommendations and perspectives: The SEIs presented here are discussed theoretically within the context of salmon food production systems, but a test of the practicability and validity of the indicators (i.e., a practical application) is also necessary. The practical application of the topic will be presented in a forthcoming paper. © 2008 Springer-Verlag.
|
|
2. |
|
|
3. |
|
|
4. |
|
|
5. |
- Flysjö, A., et al.
(author)
-
How does co-product handling affect the carbon footprint of milk? Case study of milk production in New Zealand and Sweden
- 2011
-
In: International Journal of Life Cycle Assessment. - : Springer Science and Business Media LLC. - 1614-7502 .- 0948-3349. ; 16:5, s. 420-430
-
Journal article (peer-reviewed)abstract
- Purpose This paper investigates different methodologies of handling co-products in life cycle assessment (LCA) or carbon footprint (CF) studies. Co-product handling can have a significant effect on final LCA/CF results, and although there are guidelines on the preferred order for different methods for handling co-products, no agreed understanding on applicable methods is available. In the present study, the greenhouse gases (GHG) associated with the production of 1 kg of energy-corrected milk (ECM) at farm gate is investigated considering co-product handling. Materials and methods Two different milk production systems were used as case studies in the investigation of the effect of applying different methodologies in coproduct handling: (1) outdoor grazing system in New Zealand and (2) mainly indoor housing system with a pronounced share of concentrate feed in Sweden. Since the cows produce milk, meat (when slaughtered), calves, manure, hides, etc., the environmental burden (here GHG emissions) must be distributed between these outputs (in the present study no emissions are attributed to hides specifically, or to manure which is recycled on-farm). Different methodologically approaches, (1) system expansion (two cases), (2) physical causality allocation, (3) economic allocation, (4) protein allocation and (5) mass allocation, are applied in the study. Results and discussion The results show large differences in the final CF number depending on which methodology has been used for accounting co-products. Most evident is that system expansion gives a lower CF for milk than allocation methods. System expansion resulted in 63- 76% of GHG emissions attributed directly to milk, while allocation resulted in 85-98%. It is stressed that meat is an important by-product from milk production and that milk and beef production is closely interlinked and therefore needs to be considered in an integrated approach. Conclusions To obtain valid LCA/CF numbers for milk, it is crucial to account for by-products. Moreover, if CF numbers for milk need to be compared, the same allocation procedure should be applied. © 2011 Springer-Verlag.
|
|
6. |
|
|
7. |
|
|
8. |
- Flysjö, A., et al.
(author)
-
The impact of various parameters on the carbon footprint of milk production in New Zealand and Sweden
- 2011
-
In: Agricultural Systems. - : Elsevier BV. - 1873-2267 .- 0308-521X. ; 104:6, s. 459-469
-
Journal article (peer-reviewed)abstract
- The carbon footprint (CF) of milk production was analysed at the farm gate for two contrasting production systems; an outdoor pasture grazing system in New Zealand (NZ) and a mainly indoor housing system with pronounced use of concentrate feed in Sweden (SE). The method used is based on the conceptual framework of lifecycle assessment (LCA), but only for greenhouse gas (GHG) emissions. National average data were used to model the dairy system in each country. Collection of inventory data and calculations of emissions were harmonised to the greatest extent possible for the two systems. The calculated CF for 1kg of energy corrected milk (ECM), including related by-products (surplus calves and culled cows), was 1.00kg carbon dioxide equivalents (CO2e) for NZ and 1.16kg CO2e for SE. Methane from enteric fermentation and nitrous oxide emissions from application of nitrogen (as fertiliser and as excreta dropped directly on the field) were the main contributors to the CF in both countries. The most important parameters to consider when calculating the GHG emissions were dry matter intake (DMI), emission factor (EF) for methane from enteric fermentation, amount of nitrogen applied and EF for direct nitrous oxide emissions from soils. By changing one parameter at a time within 'reasonable' limits (i.e. no extreme values assumed), the impact on the total CF was assessed and showed changes of up to 15%. In addition, the uncertainty in CF estimates due to uncertainty in EF for methane from enteric fermentation and nitrous oxide emissions (from soil and due to ammonia volatilisation) were analysed through Monte Carlo simulation. This resulted in an uncertainty distribution corresponding to 0.60-1.52kg CO2e kg-1 ECM for NZ and 0.83-1.56kg CO2e kg-1 ECM for SE (in the prediction interval 2.5-97.5%). Hence, the variation within the systems based on the main EF is relatively large compared with the difference in CF between the countries. © 2011 Elsevier Ltd.
|
|
9. |
- Flysjö, A., et al.
(author)
-
The interaction between milk and beef production and emissions from land use change - Critical considerations in life cycle assessment and carbon footprint studies of milk
- 2012
-
In: Journal of Cleaner Production. - : Elsevier BV. - 0959-6526 .- 1879-1786. ; 28, s. 134-142
-
Journal article (peer-reviewed)abstract
- Two most critical factors to address in environmental system analysis of future milk production are 1) the link between milk and beef production, and 2) the competition for land, possibly leading to land use change (LUC) with greenhouse gas (GHG) emissions and loss of biodiversity as important implications. Different methodological approaches concerning these factors, in studies on environmental impacts of dairy production, sometimes lead to contradictory results. Increasing milk yield per cow is often one of the solutions discussed in order to reduce GHG emissions from milk production. However, when also accounting for other systems affected (e.g. beef production) it is not certain that an increase in milk yield per cow leads to a reduction in total GHG emissions per kg milk. In the present study the correlation between carbon footprint (CF) of milk and the amount of milk delivered per cow is investigated for 23 dairy farms (both organic and conventional) in Sweden. Use of a fixed allocation factor of 90% (based on economic value) indicates a reduction in CF with increased milk yield, while no correlation can be noted when system expansion is applied. The average CF for two groups of farms, organic and high yielding conventional, is also calculated. When conducting system expansion the CF is somewhat lower for the organic farms (which have a lower milk yield per cow, but more meat per kg milk), but when a 90% allocation factor is used, the CF is somewhat higher for the organic farms compared to the high yielding conventional farms. In analysis of future strategies for milk production, it is suggested that system expansion should be applied, in order to also account for environmental impacts from affected systems. Thus, scenarios for milk and meat production should be analysed in an integrated approach in order to reduce total emissions from the livestock sector. How to account for emissions from LUC is highly debated and there is no current shared consensus. Different LUC methods result in significantly different results. In this study, four different LUC methods are applied, using data for organic milk production and high yielding conventional milk production systems in Sweden. Depending on which LUC method was applied, the organic system showed about 50% higher or 40% lower CF compared to the conventional high yielding system. Thus, when reporting CF numbers, it is important to report LUC-factors separately and clearly explain the underlying assumptions, since the method of accounting for LUC can drastically change the results. © 2011 Elsevier Ltd. All rights reserved.
|
|
10. |
- Henriksson, Maria, et al.
(author)
-
Variation in carbon footprint of milk due to management differences between Swedish dairy farms
- 2011
-
In: Animal. - 1751-7311 .- 1751-732X. ; 5:9, s. 1474-1484
-
Journal article (peer-reviewed)abstract
- To identify mitigation options to reduce greenhouse gas (GHG) emissions from milk production (i.e. the carbon footprint (CF) of milk), this study examined the variation in GHG emissions among dairy farms using data from previous CF studies on Swedish milk. Variations between farms in these production data, which were found to have a strong influence on milk CF, were obtained from existing databases of 1051 dairy farms in Sweden in 2005. Monte Carlo (MC) analysis was used to analyse the impact of variations in seven important parameters on milk CF concerning milk yield (energy-corrected milk (ECM) produced and delivered), feed dry matter intake (DMI), enteric CH4 emissions, N content in feed DMI, N-fertiliser rate and diesel used on farm. The largest between-farm variations among the analysed production data were N-fertiliser rate (kg/ha) and diesel used (l/ha) on farm (CV = 31% to 38%). For the parameters concerning milk yield and feed DMI, the CV was approximately 11% and 8%, respectively. The smallest variation in production data was found for N content in feed DMI. According to the MC analysis, these variations in production data led to a variation in milk CF of between 0.94 and 1.33 kg CO2 equivalents (CO2e)/kg ECM, with an average value of 1.13 kg CO2e/kg ECM. We consider that this variation of ±17%, which was found to be based on the used farm data, would be even greater if all Swedish dairy farms were included, as the sample of farms in this study was not totally unbiased. The variation identified in milk CF indicates that a potential exists to reduce GHG emissions from milk production on both the national and farm levels through changes in management. As milk yield and feed DMI are two of the most influential parameters for milk CF, feed conversion efficiency (i.e. units ECM produced/unit DMI) can be used as a rough key performance indicator for predicting CF reductions. However, it must be borne in mind that feeds have different CF due to where and how they are produced. © 2011 The Animal Consortium.
|
|
11. |
- Pelletier, N.L., et al.
(author)
-
Impact categories for life cycle assessment research of seafood production systems : Review and prospectus
- 2007
-
In: The International Journal of Life Cycle Assessment. - : Springer Science and Business Media LLC. - 0948-3349 .- 1614-7502. ; 12:6, s. 414-421
-
Journal article (peer-reviewed)abstract
- Goal, Scope and Background. In face of continued declines in global fisheries landings and concurrent rapid aquaculture development, the sustainability of seafood production is of increasing concern. Life Cycle Assessment (LCA) offers a convenient means of quantifying the impacts associated with many of the energetic and material inputs and outputs in these industries. However, the relevant but limited suite of impact categories currently used in most LCA research fails to capture a number of important environmental and social burdens unique to fisheries and aquaculture. This article reviews the impact categories used in published LCA research of seafood production to date, reports on a number of methodological innovations, and discusses the challenges to and opportunities for further impact category developments. Main Features. The range of environmental and socio-economic impacts associated with fisheries and aquaculture production are introduced, and both the commonly used and innovative impact categories employed in published LCA research of seafood production are discussed. Methodological innovations reported in agricultural LCAs are also reviewed for possible applications to seafood LCA research. Challenges and options for including additional environmental and socioeconomic impact categories are explored. Results. A review of published LCA research in fisheries and aquaculture indicates the frequent use of traditional environmental impact categories as well as a number of interesting departures from the standard suite of categories employed in LCA studies in other sectors. Notable examples include the modeling of benthic impacts, by-catch, emissions from anti-fouling paints, and the use of Net Primary Productivity appropriation to characterize biotic resource use. Socio-economic impacts have not been quantified, nor does a generally accepted methodology for their consideration exist. However, a number of potential frameworks for the integration of such impacts into LCA have been proposed. Discussion. LCA analyses of fisheries and aquaculture call attention to an important range of environmental interactions that are usually not considered in discussions of sustainability in the seafood sector. These include energy use, biotic resource use, and the toxicity of anti-fouling paints. However, certain important impacts are also currently overlooked in such research. While prospects clearly exist for improving and expanding on recent additions to environmental impact categories, the nature of the LCA framework may preclude treatment of some of these impacts. Socio-economic impact categories have only been described in a qualitative manner. Despite a number of challenges, significant opportunities exist to quantify several important socio-economic impacts. Conclusion. The limited but increasing volume of LCA research of industrial fisheries and aquaculture indicates a growing interest in the use of LCA methodology to understand and improve the sustainability performance of seafood production systems. Recent impact category innovations, and the potential for further impact category developments that account for several of the unique interactions characteristic of fisheries and aquaculture will significantly improve the usefulness of LCA in this context, although quantitative analysis of certain types of impacts may remain beyond the scope of the LCA framework. The desirability of incorporating socio-economic impacts is clear, but such integration will require considerable methodological development. Recommendations and Perspectives. While the quantity of published LCA research for seafood production systems is clearly increasing, the influence this research will have on the ground remains to be seen. In part, this will depend on the ability of LCA researchers to advance methodological innovations that enable consideration of a broader range of impacts specific to seafood production. It will also depend on the ability of researchers to communicate with a broader audience than the currently narrow LCA community. © 2007 ecomed publishers (Verlagsgruppe Hüthig Jehle Rehm GmbH).
|
|
12. |
- Pelletier, N., et al.
(author)
-
Not all salmon are created equal : Life cycle assessment (LCA) of global salmon farming systems
- 2009
-
In: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 43:23, s. 8730-8736
-
Journal article (peer-reviewed)abstract
- We present a global-scale life cycle assessment of a major food commodity, farmed salmon. Specifically, we report the cumulative energy use, biotic resource use, and greenhouse gas, acidifying, and eutrophying emissions associated with producing farmed salmon in Norway, the UK, British Columbia (Canada), and Chile, as well as a production-weighted global average. We found marked differences in the nature and quantity of material/energy resource use and associated emissions per unit production across regions. This suggests significant scope for improved environmental performance in the industry as a whole. We identify key leverage points for improving performance, most notably the critical importance of least-environmental cost feed sourcing patterns and continued improvements in feed conversion efficiency. Overall, impacts were lowest for Norwegian production in most impact categories, and highest for UK farmed salmon. Our results are of direct relevance to industry, policy makers, eco-labeling programs, and consumers seeking to further sustainability objectives in salmon aquaculture. © 2009 American Chemical Society.
|
|